Data-Driven 3D Primitives for Single Image Understanding

David Fouhey, Abhinav Gupta, and Martial Hebert
International Conference on Computer Vision, December, 2013.


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Abstract
What primitives should we use to infer the rich 3D world behind an image? We argue that these primitives should be both visually discriminative and geometrically informative and we present a technique for discovering such primitives. We demonstrate the utility of our primitives by using them to infer 3D surface normals given a single image. Our technique substantially outperforms the state-of-the-art and shows improved cross-dataset performance.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Text Reference
David Fouhey, Abhinav Gupta, and Martial Hebert, "Data-Driven 3D Primitives for Single Image Understanding," International Conference on Computer Vision, December, 2013.

BibTeX Reference
@inproceedings{Fouhey_2013_7500,
   author = "David Fouhey and Abhinav Gupta and Martial Hebert",
   title = "Data-Driven 3D Primitives for Single Image Understanding",
   booktitle = "International Conference on Computer Vision",
   month = "December",
   year = "2013",
}